Noise has long been an environmental issue that has drawn a great deal of attention. Noise control methods at present may be categorized into two types: Passive noise control and active noise control (ANC). The passive noise control refers to using barriers or sound absorbing materials, such as sound-absorbing cotton, to block the sound source to achieve the effect of cancelling noise. This method emphasizes cancelling high frequency noise, but is not suitable for cancelling noise at low frequencies. However the active noise control complements this disadvantage by using the second sound source to play an anti-noise sound source to cancel a low frequency noise.
The framework of the active noise control may be divided into feedforward control, feedback control, and hybrid control. In terms of the feedforward control framework of the active noise control, usually an adaptive algorithm is used to design a controller, such as using the least-mean-square (LMS) to practice. With the advancement of technology, the input signal, namely the reference signal, has to be filtered by passing through the secondary path to ensure convergence. The FXLMS (filtered-x least-mean-square) algorithm is widely applied to tackle the problem of active noise cancelling. Although using the aforementioned method to design a controller helps find an optimal solution and converge to a certain range, an error still occurs, leading to defects in the accuracy and effectiveness of cancelling noises.
In view of what is mentioned above, conventional active duct noise control systems still have room for improvement. Therefore, the present disclosure aims to improve deficiencies in terms of current techniques by designing an active duct noise control system and a method thereof to make the active noise control more accurate and effective so as to enhance the implementation and application in industries.